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Recent trends show a growing demand for improved powertrain NVH and sound quality. In particular, there is little customer acceptance of tonal annoyances under any driving condition. Thus, powertrain NVH and product development engineers have a strong need to confidently determine acceptable noise levels for commodities that produce narrow band noise. Components such as power steering, transmission gears, pumps, engine timing chains, axle gearing, etc., all may produce significant tones under various vehicle conditions. The perception of the tone is highly influenced by its frequency and background noise. Background noise is composed of wind, road, and engine noise. A methodology and toolset of masking perception algorithms has been developed to meet these needs. The Masking Perception Analysis Software (MPAS) is used to address the development and verification of acceptable powertrain tonal levels as well as the diagnosis of tonal-related issues.

A wavelet-based technique for reducing the impulsive character of sound recordings is presented. The amount of impulsive content removed may be adjusted by varying a statistical threshold. The technique is validated for a diesel idle sound-quality application. The wavelet-based modification produces a substantial decrease in impulsive character as verified by an objective sound-quality metric for engine “ticking”. Informal subjective assessment of the modified results found them to be realistic and free from artifacts. The procedure is expected to be useful for sound-quality simulation and target-setting for diesel powertrain noise and other automotive sounds containing both impulsive and non-impulsive content.